| Species | female | male |
|---|---|---|
| Adelie | 73 | 73 |
| Chinstrap | 34 | 34 |
| Gentoo | 58 | 61 |
Univariate Statistics involves only one variable.
Bivariate Statistics involves only two variables.
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Frequency distribution
Proportion (p)
\(p = f / n\)
f = raw frequency
n = total sample size
Percentage (pct)
\(p = (f / n)100\)
f = raw frequency
n = total sample size
Rate (r)
\(r = (f/N)Multiplier\)
f = frequency
N = population
Multiplier = determined by our population size (e.g., if your population is millions, you’d use 100,000)
A table showing overlap between two variables.
The top Columns and furthest left Rows are our variables.
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A table showing overlap between two variables.
| Species | female | male |
|---|---|---|
| Adelie | 73 | 73 |
| Chinstrap | 34 | 34 |
| Gentoo | 58 | 61 |
Used for categorical variables with only a few groups.
Adding percentages to pie charts
Used for categorical variables that have many or a few groups.
Used for continuous variables
Used for continuous variables.
Alternative to a histogram.
These are common for longitudinal variables or trends.
When using categorical graphs, what types of variables can we use?
A.) Ratio and Ordinal
B.) Interval and Nominal
C.) Nominal and Ordinal
D.) None of the above
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